Image analysis apparatus, method, and program

ABSTRACT

A storage unit stores at least one first analysis result generated by performing at least one first analysis process on an image of a subject and recovery information enabling recovery of a first analysis state where the first analysis result is generated or link information to the recovery information in a database in association with subject information specifying the subject. An analysis unit generates, in a case where at least one second analysis process generating at least one second analysis result different from the first analysis result is performed, the second analysis result by performing the second analysis process using the recovery information. The storage unit stores the second analysis result in the database in association with the subject information.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a Continuation of PCT InternationalApplication No. PCT/JP2017/036665 filed on Oct. 10, 2017, which claimspriority under 35 U.S.C. § 119(a) to Japanese Patent Application No.2016-208331 filed on Oct. 25, 2016. Each of the above applications ishereby expressly incorporated by reference, in its entirety, into thepresent application.

BACKGROUND Technical Field

The technology of the present disclosure relates to an image analysisapparatus, a method, and a program performing an analysis process on animage and storing an analysis result generated by the analysis processin a database.

Related Art

In recent years, high quality high resolution 3-dimensional images havebeen used in diagnostic imaging along with advances in medicalapparatuses such as a computed tomography (CT) apparatus and a magneticresonance imaging (MRI) apparatus. In addition, by analyzing such a3-dimensional image, 3-dimensional shapes of various organs present in abody can be obtained. Furthermore, a relative positional relationshipand a solid structure of each tissue of arteries, veins, tumors, and thelike present in the organ can be obtained. In this case, a specificorgan and a specific structure inside the organ are extracted usingvarious image processing algorithms, and their solid structures areobtained by projecting the 3-dimensional shapes to a 2-dimensional planeusing a display method such as volume rendering (VR). In addition, atumor or the like is extracted by analyzing the image usingcomputer-aided diagnosis (CAD), and the size, type, and the like of thetumor are obtained as an analysis result. The analysis result generatedby the analysis process is stored in a database in association withsubject information such as a patient name, sex, and age and is used indiagnosis.

Various methods for storing the analysis result in the database havebeen suggested. For example, JP2003-271924A suggests a method of storinginformation related to the type of process module performing theanalysis process, a parameter used by the process module, the type oftemplate used in analysis, and the like in the database along with theanalysis result. According to the method disclosed in JP2003-271924A,the same process as that in the case of generating the stored analysisresult can be performed again using the information stored along withthe analysis result.

An item that has not been previously included in the analysis result maybe newly added to the analysis result due to a version update ofsoftware for performing the analysis process. For example, in an oldversion of the software, a representative value such as the averagevalue of signal values in the tumor is not calculated. However, in acase where the representative value of the signal values of the tumor isnewly calculated due to a version update, the representative value ofthe signal values in the tumor is newly added to the analysis result. Inthis case, the added item is not present in the past analysis resultstored in the database, and the added item cannot be used in the pastanalysis result unless a user adds the new item to the database. Inaddition, in a case where analysis performance is improved by theversion update of the software, indicators of the analysis differbetween the past analysis result stored in the database and a newanalysis result. In this case, comparison between the past analysisresult and the new analysis result, and statistic analysis using thepast analysis result and the new analysis result may not be accuratelyperformed.

SUMMARY

The analysis process can be performed again using the method disclosedin JP2003-271924A. However, performing the analysis process again leadsto an increase in calculation amount, and the load of the process of theanalysis apparatus is high.

The technology of the present disclosure is conceived in view of such amatter. An object of the technology of the present disclosure is toenable a new analysis result to be stored in a database while reducing acalculation amount.

An image analysis apparatus according to the present disclosurecomprises storage unit for storing at least one first analysis resultgenerated by performing at least one first analysis process on an imageof a subject and recovery information enabling recovery of a firstanalysis state where the first analysis result is generated or linkinformation to the recovery information in a database in associationwith subject information specifying the subject, and analysis unit forgenerating, in a case where at least one second analysis processgenerating at least one second analysis result different from the firstanalysis result is performed, the second analysis result by performingthe second analysis process using the recovery information. The storageunit stores the second analysis result in the database in associationwith the subject information.

The “analysis state” is a state of analysis in a case where the firstanalysis result is generated by performing the first analysis process onthe image. For example, a state where various processes are performed onthe image until an analysis result is acquired is the analysis state.For example, in a case where a specific structure inside the subject isextracted, a state where the specific structure is extracted by ananalysis process of extracting the specific structure is the analysisstate.

The “recovery information” is information that enables recovery of thefirst analysis state by referring to the recovery information, and isinformation including an analysis history representing the processcontent and the process result of the first analysis process.Specifically, an algorithm of the analysis process, the version ofsoftware performing the analysis process, an image used in the analysisprocess in a case where the image includes a plurality of images like a3-dimensional image, an image displayed in the analysis process, theextraction result of a structure in a case where a structure isextracted from the image by the analysis process, the extraction resultof a lesion in a case where a lesion such as a tumor is extracted fromthe image by the analysis process, and the like can be used as therecovery information.

In the image analysis apparatus according to the present disclosure, theanalysis unit may recover the first analysis state based on the recoveryinformation and perform the second analysis process using the firstanalysis state.

In addition, the image analysis apparatus according to the presentdisclosure may further comprise search unit for searching the databasefor the second analysis result. The analysis unit may perform the secondanalysis process only in a case where only the first analysis result isassociated and the recovery information or the link information isassociated with the first analysis result.

In addition, in the image analysis apparatus according to the presentdisclosure, the analysis unit may calculate reliability of the secondanalysis result. The storage unit may store the second analysis resultin the database only in a case where the reliability satisfies a storagecondition for the database.

In addition, in the image analysis apparatus according to the presentdisclosure, the analysis unit may calculate reliability of the secondanalysis result. The storage unit may storage the reliability in thedatabase in association with the second analysis result.

In addition, in the image analysis apparatus according to the presentdisclosure, the storage unit may store the second analysis result in thedatabase in addition to the first analysis result.

In addition, in the image analysis apparatus according to the presentdisclosure, the storage unit may store the second analysis result in thedatabase instead of the first analysis result.

An image analysis method according to the present disclosure comprisesstoring at least one first analysis result generated by performing atleast one first analysis process on an image of a subject and recoveryinformation enabling recovery of a first analysis state where the firstanalysis result is generated or link information to the recoveryinformation in a database in association with subject informationspecifying the subject, generating, in a case where at least one secondanalysis process generating at least one second analysis resultdifferent from the first analysis result is performed, the secondanalysis result by performing the second analysis process using therecovery information, and storing the second analysis result in thedatabase in association with the subject information.

The image analysis method according to the present disclosure may beprovided as a program for causing a computer to execute the imageanalysis method.

Another image analysis apparatus according to the present disclosurecomprises a memory that stores an instruction to be executed by acomputer, and a processor that is configured to execute the storedinstruction. The processor executes a process of storing at least onefirst analysis result generated by performing at least one firstanalysis process on an image of a subject and recovery informationenabling recovery of a first analysis state where the first analysisresult is generated or link information to the recovery information in adatabase in association with subject information specifying the subject,generating, in a case where at least one second analysis processgenerating at least one second analysis result different from the firstanalysis result is performed, the second analysis result by performingthe second analysis process using the recovery information, and storingthe second analysis result in the database in association with thesubject information.

According to the present disclosure, in a case where at least one secondanalysis process generating at least one second analysis resultdifferent from the first analysis result is performed, the secondanalysis result is generated by performing the second analysis processusing the recovery information enabling recovery of the first analysisstate where the first analysis result is generated. The second analysisresult is stored in the database in association with the subjectinformation. Thus, by referring to the first analysis state in the caseof performing the second analysis process, a process performed in thefirst analysis process is not performed again, and only a process newlyadded to the second analysis process may be performed. Accordingly, acalculation amount for performing the second analysis process can bereduced, and the second analysis result can be stored in the database.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a hardware configuration diagram illustrating a summary of adiagnosis support system to which an image analysis apparatus accordingto an embodiment of the present invention is applied.

FIG. 2 is a diagram illustrating a schematic configuration of the imageanalysis apparatus.

FIG. 3 is a diagram illustrating an example of data stored in adatabase.

FIG. 4 is a flowchart illustrating a process performed at the time ofanalysis in a first embodiment.

FIG. 5 is a diagram illustrating an example of data stored in thedatabase.

FIG. 6 is a flowchart illustrating a process performed at the time ofsearch in the first embodiment.

FIG. 7 is a diagram illustrating a search result in the firstembodiment.

FIG. 8 is a diagram illustrating a search result in the firstembodiment.

FIG. 9 is a flowchart illustrating a process performed at the time ofsearch in a second embodiment.

FIG. 10 is a diagram illustrating a search result in the secondembodiment.

FIG. 11 is a diagram illustrating a search result in the secondembodiment.

FIG. 12 is a diagram illustrating the database storing a second analysisresult along with a first analysis result.

FIG. 13 is a diagram illustrating another search result in the secondembodiment.

FIG. 14 is a flowchart illustrating a process performed at the time ofsearch in a third embodiment.

FIG. 15 is a diagram illustrating a database storing data in amodification example of the third embodiment.

FIG. 16 is a diagram illustrating a search result in the modificationexample of the third embodiment.

FIG. 17 is a flowchart illustrating a process performed at the time ofsearch in a fourth embodiment.

FIG. 18 is a diagram illustrating a database storing data in amodification example of the fourth embodiment.

FIG. 19 is a diagram illustrating a search result in the modificationexample of the fourth embodiment.

DETAILED DESCRIPTION

Hereinafter, embodiments of the present invention will be described withreference to the drawings. FIG. 1 is a hardware configuration diagramillustrating a summary of a diagnosis support system to which an imageanalysis apparatus according to a first embodiment of the presentinvention is applied. As illustrated in FIG. 1, in the diagnosis supportsystem, an image analysis apparatus 1 according to the first embodiment,a 3-dimensional image capture apparatus 2, and a first server 3 areconnected in a state capable of communicating through a network 4. Inaddition, a second server 5 for storing a snapshot described below isconnected to the network 4. In the image analysis apparatus 1 of thediagnosis support system, a 3-dimensional image of a subject isanalyzed, and an analysis result is transmitted and stored in the firstserver 3.

The 3-dimensional image capture apparatus 2 is an apparatus thatgenerates a 3-dimensional image representing a diagnosis target part byimaging the diagnosis target part of the subject. Specifically, the3-dimensional image capture apparatus 2 is a CT apparatus, an MRIapparatus, a positron emission tomography (PET) apparatus, and the like.The 3-dimensional image generated by the 3-dimensional image captureapparatus 2 is transmitted to the first server 3 and stored. In thepresent embodiment, the diagnosis target part of a patient who is thesubject is a liver. The 3-dimensional image capture apparatus 2 is a CTapparatus. A CT image of the abdomen of the subject is generated as the3-dimensional image.

The first server 3 is a computer storing and managing various data andcomprises a high capacity external storage device and databasemanagement software. The first server 3 communicates with anotherapparatus through the wired or wireless network 4 and transmits andreceives image data and various information. Specifically, image datasuch as the 3-dimensional image generated by the 3-dimensional imagecapture apparatus 2 and various data including the analysis result inthe image analysis apparatus 1 are acquired through the network and arestored and managed in a recording medium such as the high capacityexternal storage device. The storage format of the image data andcommunication between each apparatus through the network 4 are based ona protocol such as digital imaging and communication in medicine(DICOM).

In the first server 3, the analysis result of the image analysisapparatus 1 is stored by a database (DB) 30 in association with a3-dimensional image G0 subjected to analysis and subject informationsuch as a patient name, sex, and age. Access to the database 30 can bemade from the image analysis apparatus 1 through the network 4. Inaddition, information stored in the database 30 can be searched from theimage analysis apparatus 1 using the patient name or the like as asearch condition.

The second server 5 is a computer storing and managing various data andcomprises a high capacity external storage device and databasemanagement software. The second server 5 communicates with anotherapparatus through the wired or wireless network 4 and stores thesnapshot or the like described below.

The image analysis apparatus 1 is implemented by installing softwarecontaining an image analysis program according to the embodiment of thepresent invention on one computer. The computer may be a workstation ora personal computer directly operated by a doctor performing diagnosis,or may be a server computer connected to the workstation or the personalcomputer through a network. The software containing the image analysisprogram is distributed as a recording on a recording medium such as adigital versatile disc (DVD) or a compact disk read only memory (CD-ROM)and is installed on the computer from the recording medium.Alternatively, the software is stored in a storage device of a servercomputer connected to a network or in a network storage in a stateenabling external access thereto and is downloaded and installed on acomputer used by a doctor as necessary.

FIG. 2 is a diagram illustrating a schematic configuration of the imageanalysis apparatus implemented by installing the software containing theimage analysis program on the computer. As illustrated in FIG. 2, theimage analysis apparatus 1 comprises a central processing unit (CPU) 11,a memory 12, and a storage 13 as a configuration of a standardworkstation. In addition, a display 14 such as a liquid crystal displayand an input unit 15 including a mouse, a keyboard, and the like areconnected to the image analysis apparatus 1.

The storage 13 stores the 3-dimensional image of the subject acquiredfrom the first server 3 through the network 4 and various informationincluding information necessary for processing. In the presentembodiment, the 3-dimensional image G0 in which the liver of the subjectis set as the diagnosis target part is stored.

In addition, the memory 12 stores the software containing the imageanalysis program. The image analysis program defines an imageacquisition process of acquiring the 3-dimensional image G0 acquired bythe 3-dimensional image capture apparatus 2, an analysis process ofanalyzing the 3-dimensional image G0, a storage process of storing theanalysis result and link information described below in the database,and a search process of searching the database as processes to beexecuted by the CPU 11.

By causing the CPU 11 to execute the processes in accordance with theprogram, the computer functions as an image acquisition unit 21, ananalysis unit 22, a storage unit 23, and a search unit 24. The imageanalysis apparatus 1 may comprise a plurality of processors orprocessing circuits performing the image acquisition process, theanalysis process, the storage process, and the search process,respectively. The image analysis apparatus 1 of the present embodimentmay be configured with only the analysis unit 22, the storage unit 23,and the search unit 24.

The image acquisition unit 21 acquires the 3-dimensional image G0 of theabdomen of the subject from the first server 3. In a case where the3-dimensional image G0 is already stored in the storage 13, the imageacquisition unit 21 may acquire the 3-dimensional image G0 from thestorage 13.

The analysis unit 22 generates the analysis result by performing theanalysis process on the 3-dimensional image G0 in accordance with theimage analysis program. In the present embodiment, the liver andsurrounding tissues such as portal veins, veins, and arteries inside theliver or around the liver are extracted from the 3-dimensional image G0.The extraction of the liver and the surrounding region may use anywell-known method. In addition, the liver and the surrounding tissuesmay be extracted from the 3-dimensional image G0 by a manual operationof an operator. In the present embodiment, the extraction of the liverand the surrounding tissues is a part of the analysis process.Furthermore, the analysis unit 22 extracts a tumor by analyzing the3-dimensional image G0 using CAD. The analysis unit 22 generates thediameter and the volume of the extracted tumor and the type and theposition of the tumor in a section of the liver as the analysis result.

The analysis unit 22 generates recovery information that enablesrecovery of an analysis state where the analysis result is generated asa snapshot. The “analysis state” is a state of analysis in a case wherethe analysis result is generated by performing the analysis process onthe 3-dimensional image G0. For example, in the present embodiment, theliver, the surrounding tissues, and the tumor are extracted by theanalysis process, and the analysis result is generated. In this case, astate where various processes such as processing the 3-dimensional imageG0 are performed or various processes are performed on the 3-dimensionalimage G0 until the analysis result is acquired is the analysis state.

The “recovery information”, that is, the snapshot, is information thatenables recovery of the analysis state performed by the analysis unit 22by referring to the recovery information, and is information includingan analysis history representing the process content and the processresult of the analysis process. In the present embodiment, the versionof the software containing the image analysis program is included in thesnapshot. In addition, since the liver, the surrounding tissues, and thetumor are extracted in the analysis process, an algorithm of theextraction of the liver, the surrounding tissues, and the tumor isincluded in the snapshot. The extraction result of the liver, thesurrounding tissues, and the tumor, that is, the 3-dimensional image ofthe extracted liver, the surrounding tissues, and the tumor, is alsoincluded in the snapshot. In addition, since the 3-dimensional image G0is configured with tomogram images in a plurality of cross sections,information specifying a tomogram image referred to or used in the caseof extracting the liver, the surrounding tissues, and the tumor is alsoincluded in the snapshot.

The storage unit 23 transmits the analysis result generated by theanalysis unit 22 to the first server 3 and stores the analysis result inthe database 30 in association with the subject information such as apatient ID, the patient name, sex, and age and the 3-dimensional imageG0. In addition, the snapshot is transmitted and stored in the secondserver 5. The link information to the snapshot stored in the secondserver 5 is stored in the database 30 of the first server 3.

FIG. 3 is a diagram illustrating an example of data stored in thedatabase. As illustrated in FIG. 3, the database 30 stores the subjectinformation, the analysis result, and the link information to thesnapshot. The subject information includes the patient ID, the patientname, sex, and age. The patient name is denoted by initials. Theanalysis result includes the diameter (simply shown as diameter) and thevolume of the tumor, the type (simply shown as type) of tumor, and thesection (simply shown as section) of the liver in which the tumor ispresent. In addition, the version of the software used in analysis isalso included in the analysis result. In the data illustrated in FIG. 3,analysis is performed using version 1.1 of the software for all patientIDs. While link information to the 3-dimensional image G0 is stored ineach data of the database 30 for association with the 3-dimensionalimage G0 used in analysis, illustration is not provided in FIG. 3 andthe subsequent description for simplification of description.

The search unit 24 searches for information stored in the database 30 inaccordance with a search condition input by the operator from the inputunit 15.

Hereinafter, processes performed in the analysis unit 22, the storageunit 23, and the search unit 24 of the present embodiment will bedescribed in detail. FIG. 4 is a flowchart illustrating a processperformed at the time of analysis in the present embodiment. First, theimage acquisition unit 21 acquires the 3-dimensional image G0 as ananalysis target (step ST1). The analysis unit 22 performs the analysisprocess on the 3-dimensional image G0 and generates the analysis result(step ST2). In this case, the snapshot is also generated. The storageunit 23 transmits and stores the snapshot in the second server 5 (stepST3) and transmits the analysis result to the first server 3 and storesthe analysis result in the database 30 in association with the3-dimensional image G0, the subject information, and the linkinformation to the snapshot (step ST4). The process is finished.

Next, a process performed at the time of search will be described. Here,an analysis function is added by a version update of the softwarecontaining the image analysis program, and a representative value ofsignal values of the tumor in the 3-dimensional image G0 is calculated.The representative value is exemplified by an average value, a maximumvalue, and a variance value. In this case, the analysis process based onthe old version of the software corresponds to a first analysis process.The analysis result generated by the first analysis process and storedin the database 30 corresponds to a first analysis result. The analysisprocess based on the new version of the software corresponds to a secondanalysis process. The analysis result generated by the second analysisprocess corresponds to a second analysis result. In a case where theversion of the software is updated, the analysis result based on the oldversion of the software coexists with the analysis result based on thenew version of the software in the database 30. For example, asillustrated in FIG. 5, while the version of the software for patients ofID 1234 and ID 1236 is 1.1, the version of the software for a patient ofID 1235 is updated to 1.2 Thus, for only the patient of ID 1235, therepresentative value of the tumor is calculated by the analysis processbased on the updated version of the software and stored in the database30.

FIG. 6 is a flowchart illustrating the process performed at the time ofsearch in the first embodiment. In a case where a search is performed,the search condition is input from the input unit 15. The sex, age, andthe like of the patient can be used as the search condition. Here, asearch condition for searching for the diameter of the tumor of apatient of any sex and any age and the representative value of thesignal values of the tumor is input. First, the search unit 24 receivesthe input of the search condition from the input unit 15 (step ST11),searches the database 30 stored in the first server 3 in accordance withthe search condition, and extracts data complying with the input searchcondition including data not storing the representative value of thesignal values as a search result candidate (step ST12).

The search unit 24 determines whether or not data that does not includethe representative value of the signal values, that is, the secondanalysis result, is present in the search result candidate (step ST13).In a case where a positive determination is made in step ST13, adetermination as to whether or not the link information to the snapshotis stored in the database 30 for the data (hereinafter, referred to astarget data) not including the representative value of the signal valuesis performed (step ST14). In a case where a positive determination ismade in step ST14, the analysis unit 22 acquires the snapshot from thelink information stored in the database 30 (step ST15) and recovers afirst analysis state that is the analysis state in the case ofgenerating the analysis result stored in the database 30, that is, thefirst analysis result (step ST16). The analysis unit 22 calculates therepresentative value of the signal values, that is, the second analysisresult, by performing the second analysis process using the recoveredfirst analysis state (step ST17). In this case, by using the firstanalysis state, the process of extracting the liver and the surroundingtissues from the 3-dimensional image G0, the process of selecting thetomogram image to extract the tumor, and a process necessary foranalysis of the 3-dimensional image G0 do not need to be performedagain. Then, the storage unit 23 transmits the second analysis result tothe first server 3 and stores the second analysis result in the database30 (step ST18). In addition, the search unit 24 generates a searchresult by adding the second analysis result to the target data (stepST19).

In a case where a negative determination is made in step ST14, thesnapshot cannot be used for the target data. Thus, for the target data,the search result is generated by adding information indicating that thesecond analysis result is not present (step ST20). In a case where anegative determination is made in step ST14, the target data may bedeleted from the search result candidate.

The search unit 24 displays the search result on the display 14 (stepST21), and the process is finished. In a case where a negativedetermination is made in step ST13, a transition is made to step ST21,and the search result candidate is displayed on the display 14 as thesearch result.

FIG. 7 is a diagram illustrating the search result in the firstembodiment. The search result includes the sex and age of the patient,the tumor diameter, and the representative value of the signal values ofthe tumor in accordance with the search condition. In the database 30illustrated in FIG. 5, the representative value of the signal values isnot calculated in the data having the patient ID of ID 1234 and ID 1236.However, since the representative value of the signal values iscalculated at the time of search, the representative value is calculatedin the data having ID 1234 in the search result. For data having thepatient ID of ID 1236, the snapshot cannot be acquired. Thus, therepresentative value is set as “none”.

The search result candidate may be displayed first on the display 14,and the second analysis process for the target data may be performed inthe background. In this case, as illustrated in FIG. 8, for data of ID1237 for which the second analysis result is being calculated,“calculating” may be displayed, and the calculation result may bedisplayed after the calculation is finished.

In the first embodiment, in a case where the second analysis process ofgenerating the representative value of the signals values of the tumor,that is, the second analysis result, not calculated in the softwarebefore the version update is performed, the first analysis state isrecovered using the snapshot enabling recovery of the first analysisstate where the first analysis result registered in the database isgenerated. The second analysis result is generated by performing thesecond analysis process using the first analysis state. The secondanalysis result is stored in the database 30. Thus, by referring to thefirst analysis state in the case of performing the second analysisprocess, the process performed in the first analysis process is notperformed again, and only a process newly added to the second analysisprocess may be performed. Accordingly, a calculation amount forperforming the second analysis process can be reduced, and the secondanalysis result can be stored in the database 30.

In addition, by performing the second analysis process on only dataassociated with the link information to the snapshot in the firstanalysis result, the second analysis process can be more efficientlyperformed.

Next, a second embodiment of the present invention will be described. Aconfiguration of an image analysis apparatus according to the secondembodiment is the same as the configuration of the image analysisapparatus according to the first embodiment illustrated in FIG. 2, andonly the performed process is different. Thus, a detailed description ofthe apparatus will not be repeated. The second embodiment is differentfrom the first embodiment in that in a case where the accuracy ofextraction of the tumor is improved by the version update of thesoftware containing the image analysis program, the tumor is extractedbased on the updated version of the software at the time of search. Theimage analysis program performs the process of extracting the liver andthe surrounding tissues. Here, the accuracy of extraction is improved byimproving the process of extracting the tumor by the version update.

FIG. 9 is a flowchart illustrating a process performed at the time ofsearch in the second embodiment. The database 30 stores the dataillustrated in FIG. 5. In the data illustrated in FIG. 5, for datahaving the patient ID of ID 1234 and ID 1236, the tumor is extractedbased on version 1.1 of the software. For data having the patient ID ofID 1235, the tumor is extracted based on updated version 1.2 of thesoftware. In addition, the search condition is the same as that in thefirst embodiment. First, the search unit 24 receives the input of thesearch condition from the input unit 15 (step ST31), searches thedatabase 30 stored in the first server 3 in accordance with the searchcondition, and extracts data complying with the search condition as thesearch result candidate (step ST32).

The search unit 24 determines whether or not data in which the diameterof the tumor is calculated based on the old version of the software ispresent (step ST33). This determination may be performed by referring tothe version of the software stored in the database 30. In a case where apositive determination is made in step ST33, a determination as towhether or not the link information to the snapshot is stored in thedatabase 30 for the data (hereinafter, referred to as target data) inwhich the diameter of the tumor is calculated based on the old versionof the software is performed (step ST34). In a case where a positivedetermination is made in step ST34, the analysis unit 22 acquires thesnapshot from the link information stored in the database 30 (step ST35)and recovers the first analysis state that is the analysis state in thecase of generating the analysis result stored in the database 30, thatis, the first analysis result (step ST36). The analysis unit 22 performsthe analysis process based on the new version of the software, that is,the second analysis process, using the recovered first analysis stateand calculates the diameter of the tumor, that is, the second analysisresult, by extracting the tumor (step ST37). In this case, by using thefirst analysis state, the process of extracting the liver and thesurrounding tissues from the 3-dimensional image G0, the process ofselecting the tomogram image to extract the tumor, and a process such asprocessing necessary for analysis of the 3-dimensional image G0 do notneed to be performed again. Then, the storage unit 23 transmits thesecond analysis result to the first server 3 and stores the secondanalysis result in the database 30 (step ST38). In this case, the secondanalysis result is stored in the database 30 instead of the firstanalysis result. In addition, the search unit 24 generates the searchresult using the second analysis result as the diameter of the tumor inthe target data (step ST39).

In a case where a negative determination is made in step ST34, thesnapshot cannot be used for the target data. Thus, for the target data,the search unit 24 generates the search result using the first analysisresult calculated based on the old version of the software and stored inthe database 30 (step ST40).

The search unit 24 displays the search result on the display 14 (stepST41), and the process is finished. In a case where a negativedetermination is made in step ST33, a transition is made to step ST41,and the search result candidate is displayed on the display 14 as thesearch result.

FIG. 10 is a diagram illustrating the search result displayed on thedisplay 14 in the second embodiment. The search result includes the sexand age of the patient and the tumor diameter in accordance with thesearch condition. In addition, the search result includes the usedversion of the software. In the database 30 illustrated in FIG. 3, fordata having the patient ID of ID 1234 and ID 1236, the diameter of thetumor is calculated based on the old version of the software. In thesearch result, the diameter of the tumor is calculated based on newversion 1.2 of the software for all data. In a case where the snapshotcannot be acquired for data having the patient ID of ID 1236 and ID1237, information related to the version and the diameter of the tumorin the data having the patient ID of ID 1236 and ID 1237 are old asillustrated in FIG. 11.

While the second analysis result is stored in the database 30 instead ofthe first analysis result in the second embodiment, the second analysisresult may be stored in the database along with the first analysisresult. FIG. 12 is a diagram illustrating the database storing thesecond analysis result along with the first analysis result. In thedatabase 30 illustrated in FIG. 12, the link information is not shownfor simplification of description. In addition, for all data, the firstanalysis process is performed based on the old version, that is, version1.1, of the software, and the first analysis result is stored in thedatabase 30. In this case, the search result includes the diameter ofthe tumor for each of the two versions as illustrated in FIG. 13.

In the database 30, the operator may correct the analysis resultcalculated by the analysis unit 22. In addition, the database 30 mayinclude the analysis result calculated by the operator. In this case, itis preferable that information indicating that the operator corrects orcalculates data is stored in the database 30. In the case of storing thesecond analysis result in the database 30 instead of the first analysisresult, it is preferable that the second analysis result is not storedin the database 30 instead of the first analysis result for data inwhich the information indicating that the operator corrects orcalculates data is stored.

Next, a third embodiment of the present invention will be described. Aconfiguration of an image analysis apparatus according to the thirdembodiment is the same as the configuration of the image analysisapparatus according to the first embodiment illustrated in FIG. 2, andonly the performed process is different. Thus, a detailed description ofthe apparatus will not be repeated. In the third embodiment, thereliability of the diameter of the tumor, that is, the second analysisresult, calculated based on the new version of the software in thesecond embodiment is calculated, and the second analysis result isstored in the database 30 only in a case where the reliability satisfiesa storage condition for the database 30.

FIG. 14 is a flowchart illustrating a process performed at the time ofsearch in the third embodiment. In the third embodiment, only theprocess after step ST37 in the flowchart of the second embodimentillustrated in FIG. 9 is different from the second embodiment. Thus,only the process after step ST37 of the flowchart illustrated in FIG. 9will be described. In a case where the second analysis result iscalculated in step ST37 of the flowchart in FIG. 9, the analysis unit 22calculates the reliability of the second analysis result for the targetdata (step ST51). Specifically, the ratio of the diameter of the tumorcalculated based on the new version of the software, that is, the secondanalysis result, to the diameter of the tumor calculated based on theold version of the software, that is, the first analysis result, iscalculated as the reliability. The storage unit 23 determines whether ornot the reliability for the target data satisfies the storage conditionfor the database (step ST52). Specifically, in a case where the secondanalysis result is greater than or equal to twice the first analysisresult and the reliability is greater than or equal to 2, or in a casewhere the second analysis result is less than or equal to ½ of the firstanalysis result and the reliability is less than or equal to ½, it isdetermined that the storage condition is not satisfied. That is, in acase where the reliability exceeds 0.5 and is less than 2, it isdetermined that the storage condition is satisfied.

In a case where a positive determination is made in step ST52, atransition is made to the process of step ST38 of the flowchartillustrated in FIG. 9, and the process from step ST38 is performed. Thatis, the storage unit 23 transmits the second analysis result to thefirst server 3 and stores the second analysis result in the database 30.The search unit 24 generates the search result using the second analysisresult and displays the search result on the display 14. The process isfinished. In a case where a negative determination is made in step ST52,a transition is made to the process of step ST40 of the flowchartillustrated in FIG. 9, and the process from step ST40 is performed. Thatis, the search result is generated using the first analysis result. Thesearch result is displayed on the display 14, and the process isfinished.

By calculating the reliability of the second analysis result and storingthe second analysis result in the database 30 only in a case where thereliability satisfies the storage condition for the database 30, only areliable analysis result can be stored in the database 30.

While the reliability of the second analysis result in the secondembodiment is calculated in the third embodiment, the reliability of thesecond analysis result in the first embodiment may be calculated. Inthis case, in a case where the representative value of the signal valuesof the tumor is calculated based on the new version of the software, thediameter of the tumor may be calculated, and the ratio of the diameterof the tumor calculated based on the new version of the software to thediameter of the tumor calculated based on the old version of thesoftware may be calculated as the reliability. In a case where thereliability does not satisfy the storage condition for the database 30,the representative value of the signal values may not be stored in thedatabase. In this case, as illustrated in FIG. 15, information “notcalculated” is stored in the database in the representative value indata having the patient ID of ID 1234 for which the reliability does notsatisfy the storage condition. In addition, the search result in thiscase is illustrated in FIG. 16. In a case where the representative valueof the signal values is not stored in the database, data having thepatient ID of ID 1234 includes information “not calculated” in therepresentative value as illustrated in FIG. 16.

Next, a fourth embodiment of the present invention will be described. Aconfiguration of an image analysis apparatus according to the fourthembodiment is the same as the configuration of the image analysisapparatus according to the first embodiment illustrated in FIG. 2, andonly the performed process is different. Thus, a detailed description ofthe apparatus will not be repeated. In the fourth embodiment, thereliability of the diameter of the tumor, that is, the second analysisresult, calculated based on the new version of the software in thesecond embodiment is calculated, and the second analysis result isstored in the database 30 along with the reliability.

FIG. 17 is a flowchart illustrating a process performed at the time ofsearch in the fourth embodiment. In the fourth embodiment, only theprocess after step ST37 in the flowchart of the second embodimentillustrated in FIG. 9 is different from the second embodiment. Thus,only the process after step ST37 of the flowchart illustrated in FIG. 9will be described. In a case where the second analysis result iscalculated in step ST37 of the flowchart in FIG. 9, the analysis unit 22calculates the reliability of the second analysis result for the targetdata in the same manner as the third embodiment (step ST61). The storageunit 23 stores the second analysis result and the reliability for thetarget data in the database (step ST62). A transition is made to theprocess of step ST39 of the flowchart illustrated in FIG. 9, and theprocess from step ST39 is performed. That is, the search unit 24generates the search result using the second analysis result. The searchresult is displayed on the display 14, and the process is finished.

FIG. 18 is a diagram illustrating the database storing the secondanalysis result and the reliability in the fourth embodiment. Asillustrated in FIG. 18, the diameter of the tumor calculated based onnew version 1.2 of the software and the reliability are stored in thedatabase 30. In the database illustrated in FIG. 18, the reliability is1.2, 1.0, and 2.4 for data having the patient ID of ID 1234, ID 1235,and ID 1236, respectively.

FIG. 19 is a diagram illustrating the search result in the fourthembodiment. As illustrated in FIG. 19, the analysis result includes thediameter of the tumor and the reliability for each of the two versions.

In the fourth embodiment, the reliability of the second analysis resultis calculated, and the reliability is stored in the database 30 inassociation with the second analysis result. Thus, a determination as towhether or not the second analysis result is reliable can be made whenthe database 30 is referred to. Particularly, in a case where it isconsidered that the image of the tumor extracted by the second analysisprocess is used as learning data of a self-learning algorithm fordetecting the tumor, appropriate learning cannot be performed in a casewhere the reliability of the analysis result is low, since theextraction of the tumor may not be accurately performed. By storing thereliability in association with the second analysis result as in thefourth embodiment, the reliability of the second analysis result can bedetermined. Thus, only a reliable second analysis result can be used asthe learning data. Accordingly, learning using the learning data can beappropriately performed.

In each embodiment, the snapshot is stored in the second server 5, andthe link information to the snapshot is stored in the database 30.Alternatively, the snapshot may be stored in the first server 3, and thesnapshot may be associated with each data stored in the database 30.

In addition, in each embodiment, the second analysis process isperformed at the time of search. Alternatively, access to the database30 from the image analysis apparatus 1 may be made per certain period oftime, and the second analysis process may be performed in a case wheredata not storing the second analysis result is present. Alternatively,access to the database 30 from the image analysis apparatus 1 may bemade in a case where the operator provides an instruction from the inputunit 15, and the second analysis process may be performed in a casewhere data not storing the second analysis result is present.

In addition, in the embodiments, the 3-dimensional image is used as thetarget of the analysis process. Alternatively, a 2-dimensional imagesuch as an X-ray image may be used as the target of analysis. Inaddition, in the embodiments, the liver is used as the target of theanalysis process. Alternatively, another organ such as a heart, a lung,or a brain may be used as the target of the analysis process.

Hereinafter, the effect of the present embodiment will be described.

By searching for the second analysis result for the image stored in thedatabase and performing the second analysis process only in a case whereonly the first analysis result is associated and the recoveryinformation or the link information is associated with the firstanalysis result, the second analysis process can be more efficientlyperformed.

By calculating the reliability of the second analysis result and storingthe second analysis result in the database only in a case where thereliability satisfies the storage condition for the database, only areliable analysis result can be stored in the database.

By calculating the reliability of the second analysis result and storingthe reliability in the database in association with the second analysisresult, a determination as to whether or not the second analysis resultis reliable can be made when the database is referred to. Particularly,in a case where it is considered that the second analysis result is usedas the learning data of the self-learning algorithm, appropriatelearning cannot be performed in a case where the reliability of theanalysis result is low. By storing the reliability in association withthe second analysis result, the reliability of the second analysisresult can be determined. Thus, only a reliable second analysis resultcan be used as the learning data. Accordingly, learning using thelearning data can be appropriately performed.

What is claimed is:
 1. An image analysis apparatus comprising: aprocessor configured to: store at least one first analysis resultgenerated by performing at least one first analysis process on an imageof a subject and recovery information enabling recovery of a firstanalysis state where the first analysis result is generated or linkinformation to the recovery information in a database in associationwith subject information specifying the subject; generate, in a casewhere at least one second analysis process generating at least onesecond analysis result different from the first analysis result isperformed, the second analysis result by performing the second analysisprocess using the recovery information; and store the second analysisresult in the database in association with the subject information. 2.The image analysis apparatus according to claim 1, wherein the processoris further configured to recover the first analysis state based on therecovery information and performs the second analysis process using thefirst analysis state.
 3. The image analysis apparatus according to claim1, wherein the processor is further configured to: search the databasefor the second analysis result, and perform the second analysis processonly in a case where only the first analysis result is associated andthe recovery information or the link information is associated with thefirst analysis result.
 4. The image analysis apparatus according toclaim 1, wherein the processor is further configured to: calculatereliability of the second analysis result, and store the second analysisresult in the database only in a case where the reliability satisfies astorage condition for the database.
 5. The image analysis apparatusaccording to claim 1, wherein the processor is further configured to:calculate reliability of the second analysis result, and store thereliability in the database in association with the second analysisresult.
 6. The image analysis apparatus according to claim 1, whereinthe processor is further configured to store the second analysis resultin the database in addition to the first analysis result.
 7. The imageanalysis apparatus according to claim 1, wherein the processor isfurther configured to store the second analysis result in the databaseinstead of the first analysis result.
 8. An image analysis methodcomprising: storing at least one first analysis result generated byperforming at least one first analysis process on an image of a subjectand recovery information enabling recovery of a first analysis statewhere the first analysis result is generated or link information to therecovery information in a database in association with subjectinformation specifying the subject; generating, in a case where at leastone second analysis process generating at least one second analysisresult different from the first analysis result is performed, the secondanalysis result by performing the second analysis process using therecovery information; and storing the second analysis result in thedatabase in association with the subject information.
 9. Anon-transitory computer-readable storage medium that stores an imageanalysis program causing a computer to execute: a procedure of storingat least one first analysis result generated by performing at least onefirst analysis process on an image of a subject and recovery informationenabling recovery of a first analysis state where the first analysisresult is generated or link information to the recovery information in adatabase in association with subject information specifying the subject;a procedure of generating, in a case where at least one second analysisprocess generating at least one second analysis result different fromthe first analysis result is performed, the second analysis result byperforming the second analysis process using the recovery information;and a procedure of storing the second analysis result in the database inassociation with the subject information.